Digma launches platform to improve code quality with AI

Digma has launched the Preemptive Observability platform, an analysis engine designed to identify issues in complex code before they reach production.

The Preemptive Observability Analysis engine provides fix suggestions to address coding issues that might otherwise manifest in system performance and reliability once the code is deployed. This approach is expected to become essential as companies increasingly adopt AI tools to aid in code generation, according to Digma.

AI-generated code has been noted to introduce more bugs, as highlighted by a 2023 Stanford University study, a trend observed even in large tech companies like Google. Digma's tool is positioned to assist by enhancing pre-production testing, offering a system that helps software developers and organisations improve code reliability.

"We're seeing a lot of effort invested in assuring optimal system performance, but many issues are still being discovered in complex code bases late in production," said Nir Shafrir, CEO and Co-founder of Digma.

"It means that engineering teams may spend between 20-40% of their time addressing issues discovered late in production environments, with some organisations spending up to 50% of engineering resources on fixing production problems. Beyond this, scaling has often remained a rough estimation in organisations anticipating growth, and many are hitting barriers in technology growth that arise precisely during periods of significant organisational expansion," Shafrir said.

Application Performance Monitoring (APM) tools have traditionally been used to manage production issues; however, they often fall short of offering insights into the root causes of problems. Digma's Preemptive Observability seeks to address this gap by proactively detecting issues earlier in the software development lifecycle.

Digma's platform utilises pattern matching and anomaly detection to flag deviations in application performance metrics. The engine can identify issues before they impact production environments, potentially providing significant improvements in productivity and cost efficiency. It accomplishes this by analysing tracing data to pinpoint specific code-level problems.

"While there are many code suggestion bots that scan code syntax, we're uniquely analysing code as it executes in a pre-production environment," explained Roni Dover, Chief Technology Officer and Co-founder of Digma. "By understanding runtime behaviour and suggesting fixes for performance issues, scaling problems, and team conflicts, we're helping enterprises prevent problems and reduce risks proactively rather than putting out fires in production."

Key features of the new analysis engine include pattern-based issue identification, AI-driven fix suggestions, team collaboration insights, cloud cost optimisation, comprehensive management dashboards, and a sandbox environment for safe evaluation without deployment.

This launch follows Digma's successful $6 million seed funding round, which reflects investor confidence in the company's approach to improving software quality. The funding will support the development of the product, focusing on addressing the specific needs of enterprise software teams, including engineering managers and directors who oversee deliverables and code quality.

Thousands of developers have already utilised Digma's free version, and the company provides a sandbox environment to trial the Preemptive Observability Analysis engine.